Senior Machine Learning Engineer; Reinforcement Learning

Senior Machine Learning Engineer (Reinforcement Learning)

This organization is looking for a Senior Machine Learning Engineer with deep expertise in Reinforcement Learning (RL) to design, build, and deploy production‑grade ML systems. The role combines hands‑on technical execution with project leadership, client collaboration, and end‑to‑end solution ownership.

• Design, implement, and deploy Reinforcement Learning solutions using real‑world data
• Own the full ML lifecycle: data strategy, model development, optimization, and productionization
• Architect scalable RL systems, including cloud‑based deployments (e.g., Google Cloud)
• Optimize model performance, training pipelines, and inference workflows
• Translate ambiguous business requirements into technical solutions
• Lead technical discussions with stakeholders and contribute to project scoping
• Ensure production‑quality code standards, CI/CD integration, and reproducibility

• 5+ years of experience as a Machine Learning Engineer, with significant RL focus
• Proven experience implementing RL algorithms (e.g., SAC, DQN, PPO) in real‑world environments
• Strong understanding of RL training dynamics, data requirements, and experimentation workflows
• Proficiency in Python and ML frameworks such as PyTorch or Tensor Flow
• Experience deploying ML systems into production environments
• Solid software engineering fundamentals and best practices

• Experience with distributed RL frameworks (e.g., Ray RLlib)
• RL applications involving Computer Vision
• Cloud platform experience (GCP, AWS, or Azure)
• Consulting or client‑facing project experience

This posting reflects an active, approved hiring need. We only advertise real roles with confirmed headcount. We use artificial intelligence tools to support parts of our screening process and identify strong alignment efficiently. Every application is reviewed by our recruitment team to ensure thoughtful, human evaluation. We believe hiring should be transparent, timely, and grounded in real opportunity.